CodeProject.AI Discussions

08:19:37:Object Detection (YOLOv5 6.2):  [RuntimeError] : Traceback (most recent call last):
  File "C:\Program Files\CodeProject\AI\modules\ObjectDetectionYOLOv5-6.2\detect.py", line 141, in do_detection
    det                  = detector(img, size=640)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 705, in forward
    y = self.model(x, augment=augment)  # forward
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\yolov5\models\common.py", line 515, in forward
    y = self.model(im, augment=augment, visualize=visualize) if augment or visualize else self.model(im)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 209, in forward
    return self._forward_once(x, profile, visualize)  # single-scale inference, train
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 121, in _forward_once
    x = m(x)  # run
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\lib\site-packages\torch\nn\modules\module.py", line 1190, in _call_impl
    return forward_call(*input, **kwargs)
  File "C:\Program Files\CodeProject\AI\runtimes\bin\windows\python37\venv\Lib\site-packages\yolov5\models\yolo.py", line 75, in forward
    wh = (wh * 2) ** 2 * self.anchor_grid[i]  # wh
RuntimeError: The size of tensor a (60) must match the size of tensor b (56) at non-singleton dimension 2

Server version:   2.5.4
System:           Docker
Operating System: Linux (Ubuntu 22.04)
CPUs:             1 CPU. (Arm64)
System RAM:       8 GiB
Platform:         RaspberryPi
BuildConfig:      Release
Execution Env:    Docker
Runtime Env:      Production
.NET framework:   .NET 7.0.16
Default Python:   3.10
Go Version:
Video adapter info:
System GPU info:
  GPU 3D Usage       0%
  GPU RAM Usage      0
Global Environment variables:
  CPAI_APPROOTPATH = <root>
  CPAI_PORT        = 32168

version: "3.8"

services:
  ai-server:
    image: codeproject/ai-server:rpi64-2.5.4
    container_name: CodeprojectAI
    privileged: true
    ports:
      - "32168:32168"
    volumes:
      - /dev/bus/usb:/dev/bus/usb
      - /data/compose/codeprojectai/data:/app/data
      - /data/compose/codeprojectai/ai:/etc/codeproject/ai
      - /data/compose/codeprojectai/modules:/app/modules

Server version:   2.5.4
System:           Linux
Operating System: Linux (Debian GNU/Linux 12)
CPUs:             Intel(R) Xeon(R) CPU E3-1220 v5 @ 3.00GHz (Intel)
                  1 CPU x 4 cores. 4 logical processors (x64)
GPU (Primary):    Tesla P4 (8 GiB) (NVIDIA) 
                  Driver: 550.54.14, CUDA: 12.4 (up to: 12.4), Compute: 6.1, cuDNN: 
System RAM:       8 GiB
Platform:         Linux
BuildConfig:      Release
Execution Env:    Native (SSH)
Runtime Env:      Production
.NET framework:   .NET 7.0.15
Default Python:   3.11
Go Version:
Video adapter info:
  Matrox Electronics Systems Ltd. G200eR2 (rev 01):
    Driver Version     
    Video Processor
System GPU info:
  GPU 3D Usage       3%
  GPU RAM Usage      1.5 GiB
Global Environment variables:
  CPAI_APPROOTPATH = <root>
  CPAI_PORT        = 32168

9:51:08:System:           Linux
09:51:08:Operating System: Linux (Debian GNU/Linux 12)
09:51:08:CPUs:             Intel(R) Xeon(R) CPU E3-1220 v5 @ 3.00GHz (Intel)
09:51:08:                  1 CPU x 4 cores. 4 logical processors (x64)
09:51:08:GPU (Primary):    Tesla P4 (8 GiB) (NVIDIA)
09:51:08:                  Driver: 550.54.14, CUDA: 12.4 (up to: 12.4), Compute: 6.1, cuDNN:
09:51:08:System RAM:       8 GiB
09:51:08:Platform:         Linux
09:51:08:BuildConfig:      Release
09:51:08:Execution Env:    Native (SSH)
09:51:08:Runtime Env:      Production
09:51:08:.NET framework:   .NET 7.0.15
09:51:08:Default Python:   3.11
09:51:08:Go Version:
09:51:08:App DataDir:      /etc/codeproject/ai
09:51:08:Video adapter info:
09:51:08:  Matrox Electronics Systems Ltd. G200eR2 (rev 01):
09:51:08:    Driver Version
09:51:08:    Video Processor
09:51:08:STARTING CODEPROJECT.AI SERVER
09:51:08:RUNTIMES_PATH             = /usr/bin/codeproject.ai-server-2.5.4/runtimes
09:51:08:PREINSTALLED_MODULES_PATH = /usr/bin/codeproject.ai-server-2.5.4/preinstalled-modules
09:51:08:MODULES_PATH              = /usr/bin/codeproject.ai-server-2.5.4/modules
09:51:08:PYTHON_PATH               = /bin/linux/%PYTHON_NAME%/venv/bin/python3
09:51:08:Data Dir                  = /etc/codeproject/ai
09:51:08:Server version:   2.5.4
09:51:08:ModuleRunner Start
09:51:08:Starting Background AI Modules
09:51:14:Current Version is 2.5.4
09:51:14:A new version 2.5.6 is available
10:03:07:API server is offline (NetworkError when attempting to fetch resource.)
10:03:49:API server is offline (NetworkError when attempting to fetch resource.)
10:03:54:API server is offline (NetworkError when attempting to fetch resource.)

10:06:57:Preparing to install module 'TrainingObjectDetectionYOLOv5'
10:06:57:Downloading module 'TrainingObjectDetectionYOLOv5'
10:06:59:Installing module 'TrainingObjectDetectionYOLOv5'
10:06:59:TrainingObjectDetectionYOLOv5: Setting verbosity to quiet
10:06:59:TrainingObjectDetectionYOLOv5: Hi Docker! We will disable shared python installs for downloaded modules
10:06:59:TrainingObjectDetectionYOLOv5: No schemas installed
10:06:59:TrainingObjectDetectionYOLOv5: (No schemas means: we can't detect if you're in light or dark mode)
10:06:59:TrainingObjectDetectionYOLOv5:              Installing CodeProject.AI Analysis Module                
10:06:59:TrainingObjectDetectionYOLOv5: ======================================================================
10:06:59:TrainingObjectDetectionYOLOv5:                    CodeProject.AI Installer                           
10:06:59:TrainingObjectDetectionYOLOv5: ======================================================================
10:06:59:TrainingObjectDetectionYOLOv5: 5.01 TiB of 8.00 TiB available on Docker
10:06:59:TrainingObjectDetectionYOLOv5: Installing xz-utils...
10:06:59:TrainingObjectDetectionYOLOv5: WARNING: apt does not have a stable CLI interface. Use with caution in scripts.
10:06:59:TrainingObjectDetectionYOLOv5: WARNING: apt does not have a stable CLI interface. Use with caution in scripts.
10:07:06:TrainingObjectDetectionYOLOv5: General CodeProject.AI setup                                          
10:07:06:TrainingObjectDetectionYOLOv5: Setting permissions on downloads folder...Done
10:07:06:TrainingObjectDetectionYOLOv5: Setting permissions on runtimes folder...Done
10:07:06:TrainingObjectDetectionYOLOv5: Setting permissions on persisted data folder...Done
10:07:06:TrainingObjectDetectionYOLOv5: GPU support                                                           
10:07:06:TrainingObjectDetectionYOLOv5: CUDA (NVIDIA) Present: No
10:07:19:TrainingObjectDetectionYOLOv5: ROCm (AMD) Present:    (attempt to install rocminfo... ) No
10:07:19:TrainingObjectDetectionYOLOv5: MPS (Apple) Present:   No
10:07:20:TrainingObjectDetectionYOLOv5: Reading module settings.......Done
10:07:20:TrainingObjectDetectionYOLOv5: Processing module TrainingObjectDetectionYOLOv5 1.6.3                 
10:07:20:TrainingObjectDetectionYOLOv5: Installing Python 3.8
10:07:20:TrainingObjectDetectionYOLOv5: Python 3.8 is already installed
10:07:39:TrainingObjectDetectionYOLOv5: Ensuring PIP in base python install...  done
10:07:47:TrainingObjectDetectionYOLOv5: Upgrading PIP in base python install... done
10:07:47:TrainingObjectDetectionYOLOv5: Virtual Environment already present
10:07:47:TrainingObjectDetectionYOLOv5: Checking for Python 3.8...(Found Python 3.8.18) All good
10:07:57:TrainingObjectDetectionYOLOv5: Upgrading PIP in virtual environment... done
10:08:07:TrainingObjectDetectionYOLOv5: Installing updated setuptools in venv... Done
10:08:11:TrainingObjectDetectionYOLOv5: Searching for libcurl4...All good.
10:08:11:TrainingObjectDetectionYOLOv5: deb http://security.ubuntu.com/ubuntu focal-security main
10:08:31:TrainingObjectDetectionYOLOv5: Searching for libssl1.1...installing...   Done
10:08:46:TrainingObjectDetectionYOLOv5: Downloading Standard YOLO models...Expanding... Done.
10:08:47:TrainingObjectDetectionYOLOv5: Moving contents of models-yolo5-pt.zip to assets...done.
10:08:47:TrainingObjectDetectionYOLOv5: Installing Python packages for Training for YoloV5 6.2
10:08:47:TrainingObjectDetectionYOLOv5: Installing GPU-enabled libraries: If available
10:08:51:TrainingObjectDetectionYOLOv5: Searching for python3-pip...All good.
10:09:03:TrainingObjectDetectionYOLOv5: Ensuring PIP compatibility... Done
10:09:03:TrainingObjectDetectionYOLOv5: Python packages will be specified by requirements.txt
10:09:10:TrainingObjectDetectionYOLOv5:   - Installing urllib3, the HTTP client for Python...Already installed
10:09:18:TrainingObjectDetectionYOLOv5:   - Installing matplotlib, the python plotting package...Already installed
10:09:25:TrainingObjectDetectionYOLOv5:   - Installing NumPy, a package for scientific computing...Already installed
10:09:33:TrainingObjectDetectionYOLOv5:   - Installing OpenCV, the Open source Computer Vision library...Already installed
10:09:40:TrainingObjectDetectionYOLOv5:   - Installing Pillow, a Python Image Library...Already installed
10:09:48:TrainingObjectDetectionYOLOv5:   - Installing PyYAML, a library for reading configuration files...Already installed
10:09:55:TrainingObjectDetectionYOLOv5:   - Installing request, the HTTP library...Already installed
10:10:03:TrainingObjectDetectionYOLOv5:   - Installing SciPy, a library for mathematics, science, and engineering...Already installed
10:10:10:TrainingObjectDetectionYOLOv5:   - Installing Torch, for Tensor computation and Deep neural networks...Already installed
10:10:18:TrainingObjectDetectionYOLOv5:   - Installing TorchVision, for Computer Vision based AI...Already installed
10:10:25:TrainingObjectDetectionYOLOv5:   - Installing tdqm, the Fast, Extensible Progress Meter...Already installed
10:10:33:TrainingObjectDetectionYOLOv5:   - Installing protobuf, extensible mechanisms for serializing structured data...Already installed
10:10:40:TrainingObjectDetectionYOLOv5:   - Installing tensorboard, a tool to let you watch Tensors Flow...Already installed
10:10:48:TrainingObjectDetectionYOLOv5:   - Installing Pandas, a data analysis / data manipulation tool...Already installed
10:10:55:TrainingObjectDetectionYOLOv5:   - Installing Seaborn, a data visualization library based on matplotlib...Already installed
10:11:03:TrainingObjectDetectionYOLOv5:   - Installing ipython, for interactive notebooks...Already installed
10:11:10:TrainingObjectDetectionYOLOv5:   - Installing psutil, a tool to check system utilization...Already installed
10:11:17:TrainingObjectDetectionYOLOv5:   - Installing thop, a tool to count the FLOPs of PyTorch model....Already installed
10:11:25:TrainingObjectDetectionYOLOv5:   - Installing Ultralytics YoloV5 package for object detection in images...Already installed
10:11:32:TrainingObjectDetectionYOLOv5:   - Installing fiftyone, for building datasets and computer vision models...Already installed
10:11:32:TrainingObjectDetectionYOLOv5: Installing Python packages for the CodeProject.AI Server SDK
10:11:37:TrainingObjectDetectionYOLOv5: Searching for python3-pip...All good.
10:11:48:TrainingObjectDetectionYOLOv5: Ensuring PIP compatibility... Done
10:11:48:TrainingObjectDetectionYOLOv5: Python packages will be specified by requirements.txt
10:11:56:TrainingObjectDetectionYOLOv5:   - Installing Pillow, a Python Image Library...Already installed
10:12:03:TrainingObjectDetectionYOLOv5:   - Installing Charset normalizer...Already installed
10:12:10:TrainingObjectDetectionYOLOv5:   - Installing aiohttp, the Async IO HTTP library...Already installed
10:12:18:TrainingObjectDetectionYOLOv5:   - Installing aiofiles, the Async IO Files library...Already installed
10:12:25:TrainingObjectDetectionYOLOv5:   - Installing py-cpuinfo to allow us to query CPU info...Already installed
10:12:32:TrainingObjectDetectionYOLOv5:   - Installing Requests, the HTTP library...Already installed
10:12:53:TrainingObjectDetectionYOLOv5: Self test: Self-test passed
10:12:53:TrainingObjectDetectionYOLOv5: Module setup time 00:05:34
10:12:53:TrainingObjectDetectionYOLOv5:                 Setup complete                                        
10:12:53:TrainingObjectDetectionYOLOv5: Total setup time 00:05:54
10:12:53:Module TrainingObjectDetectionYOLOv5 installed successfully.
10:12:53:Installer exited with code 0
10:12:53:Module TrainingObjectDetectionYOLOv5 not configured to AutoStart.
10:13:19:Update TrainingObjectDetectionYOLOv5. Setting AutoStart=true
10:13:19:Restarting Training for YoloV5 6.2 to apply settings change
10:13:19:
10:13:19:Module 'Training for YoloV5 6.2' 1.6.3 (ID: TrainingObjectDetectionYOLOv5)
10:13:19:Valid:         True
10:13:19:Module Path:   <root>/modules/TrainingObjectDetectionYOLOv5
10:13:19:AutoStart:     True
10:13:19:Queue:         trainingobjectdetectionyolov5_queue
10:13:19:Runtime:       python3.8
10:13:19:Runtime Loc:   Local
10:13:19:FilePath:      training_objectdetection_YOLOv5_adapter.py
10:13:19:Pre installed: False
10:13:19:Start pause:   1 sec
10:13:19:Parallelism:   2
10:13:19:LogVerbosity:
10:13:19:Platforms:     all,!raspberrypi,!orangepi,!jetson
10:13:19:GPU Libraries: installed if available
10:13:19:GPU Enabled:   enabled
10:13:19:Accelerator:
10:13:19:Half Precis.:  enable
10:13:19:Environment Variables
10:13:19:FIFTYONE_DATABASE_DIRNAME = fiftyone
10:13:19:YOLOv5_AUTOINSTALL        = false
10:13:19:YOLOv5_VERBOSE            = false
10:13:19:YOLO_DATASETS_DIRNAME     = datasets
10:13:19:YOLO_DATASET_ZOO_DIRNAME  = zoo
10:13:19:YOLO_MODELS_DIRNAME       = assets
10:13:19:YOLO_TRAINING_DIRNAME     = train
10:13:19:YOLO_WEIGHTS_DIRNAME      = weights
10:13:19:
10:13:19:Started Training for YoloV5 6.2 module
10:13:46:training_objectdetection_YOLOv5_adapter.py: Subprocess ['/app/modules/TrainingObjectDetectionYOLOv5/bin/linux/python38/venv/lib/python3.8/site-packages/fiftyone/db/bin/mongod', '--dbpath', '/app/modules/TrainingObjectDetectionYOLOv5/fiftyone', '--logpath', '/app/modules/TrainingObjectDetectionYOLOv5/fiftyone/log/mongo.log', '--port', '0', '--nounixsocket'] exited with error -4:
10:14:34:detect_adapter.py: YOLOv5.1m summary: 391 layers, 21805053 parameters, 0 gradients
10:14:34:detect_adapter.py: Adding AutoShape... 
10:14:39:training_objectdetection_YOLOv5_adapter.py: Unable to import and initialise the fiftyone.zoo package: fiftyone.core.service.DatabaseService failed to bind to port
10:14:42:Module TrainingObjectDetectionYOLOv5 has shutdown
10:14:42:training_objectdetection_YOLOv5_adapter.py: has exited

Server version:   2.5.6
System:           Docker
Operating System: Linux (Ubuntu 22.04)
CPUs:             Intel(R) Atom(TM) CPU  C2538  @ 2.40GHz (Intel)
                  1 CPU x 4 cores. 4 logical processors (x64)
System RAM:       8 GiB
Platform:         Linux
BuildConfig:      Release
Execution Env:    Docker
Runtime Env:      Production
Runtimes installed:
  .NET runtime:     7.0.16
  .NET SDK:         Not found
  Default Python:   Not found
  Go:               Not found
  NodeJS:           Not found
Video adapter info:
System GPU info:
  GPU 3D Usage       0%
  GPU RAM Usage      0
Global Environment variables:
  CPAI_APPROOTPATH = <root>
  CPAI_PORT        = 32168

/bin/bash: line 1: pstree: command not found
Unhandled exception. System.Collections.Generic.KeyNotFoundException: The given key 'version' was not present in the dictionary.
   at System.Collections.Generic.Dictionary`2.get_Item(TKey key)
   at CodeProject.AI.SDK.Common.SystemInfo.GetRuntimesAsync()
   at CodeProject.AI.SDK.Common.SystemInfo.InitializeAsync()
   at CodeProject.AI.Server.Program.Main(String[] args)
   at CodeProject.AI.Server.Program.<Main>(String[] args)